Yihong Guo

STUDY QUESTION: Are there distinct variations in the gut microbiome and metabolism among infertile women diagnosed with diminished ovarian reserve (DOR), and how might the gut microbiome influence ovarian function? SUMMARY ANSWER: In DOR patients, Hoylesella abundance correlated with anti-Müllerian hormone (AMH)/antral follicle count (AFC), and stearic acid was identified as a key differential metabolite that was associated with activated PI3K-Akt signaling. WHAT IS KNOWN ALREADY: Accumulating evidence underscores the presence of a ‘gut-ovary axis’, highlighting a substantial interplay between the intestinal microbiome and ovarian function. However, the specific microbial and metabolic profiles characterizing infertile individuals with DOR remain largely uncharacterized. STUDY DESIGN, SIZE, DURATION: This study was a cross-sectional observational study. We enrolled participants receiving frozen embryo transfer at the First Affiliated Hospital of Zhengzhou University between 1 October 2024, and 31 December 2025. Each participant was limited to a single frozen embryo transfer within the study. PARTICIPANTS/MATERIALS, SETTING, METHODS: A total of 190 participants were included: 91 with DOR and 99 with normal ovarian reserve (NOR). Clinical information and stool specimens were collected from every subject. Sequencing of 16S rRNA and non-targeted metabolomics were implemented to characterize the gut microbiome and metabolome, respectively. Molecular docking analysis and network pharmacology were then implemented to screen for overlapping genetic targets among DOR-associated targets and key metabolite-targeted proteins. MAIN RESULTS AND THE ROLE OF CHANCE: Relative to NOR controls, the DOR population exhibited significantly lower Gut Microbiota Health Index (P = 2.52 × 10−22) and higher Microbiota Dysbiosis Index (P = 8.31 × 10−10). The genus Hoylesella was significantly depleted in the DOR group (P = 0.018). Spearman analysis demonstrated that Hoylesella proportions were significantly positively correlated with AMH and AFC levels. Metabolomics analysis identified 243 differential metabolites across the study cohorts. Among these, four metabolites were associated with Hoylesella, and stearic acid exhibited high predictive performance (area under the curve = 0.89) for distinguishing DOR. Network pharmacology analysis of stearic acid and DOR identified five core targets: tumor necrosis factor, AKT serine/threonine kinase 1, SRC proto-oncogene, non-receptor tyrosine kinase (SRC), peroxisome proliferator-activated receptor gamma (PPARG), and epidermal growth factor receptor. Kyoto Encyclopedia of Genes and Genomes pathway enrichment indicated that the PI3K-Akt signaling pathway was the most significantly enriched. LARGE SCALE DATA: Raw 16S rRNA sequencing data have been deposited in the NCBI Sequence Read Archive under BioProject accession PRJNA1444490. Untargeted metabolomics data have been deposited in MetaboLights under accession MTBLS14194. LIMITATIONS, REASONS FOR CAUTION: The current investigation represents an initial effort to identify the alterations in intestinal microbes and associated metabolites in women with DOR-related infertility through 16S rRNA sequencing and untargeted metabolomics; however, experimental validation of the underlying mechanisms is still missing. Furthermore, the metabolomics analysis in this study did not further stratify by age. WIDER IMPLICATIONS OF THE FINDINGS: Through immunological dysregulation and inflammatory reactions, aberrant alterations in key intestinal microbes and metabolic products likely participate in the underlying mechanisms of DOR. These results provide direction for further research into the causal connections between important microbial species and metabolites in patients with DOR. FUNDING: This research was supported by grant 32271169 from the National Natural Science Foundation of China and the Henan Province Young and Middle-aged Health Science and Technology Innovation Leading Talent Project (Grant No. LJRC2024009). DISCLOSURES: The authors have no conflicts of interest. TRIAL REGISTRATION NUMBER: N/A.

Background: Male reproductive abnormalities have been reported in autosomal dominant polycystic kidney disease (ADPKD), but their impact on embryo development and clinical outcomes after preimplantation genetic testing remains unclear. Objectives: This study aimed to evaluate the association of male and female ADPKD with embryologic and clinical outcomes in preimplantation genetic testing for monogenic disorder (PGT‐M) cycles, and to explore whether progressive sperm motility modifies the association between male ADPKD and embryo developmental outcomes. Materials/Methods: This retrospective cohort study included 490 PGT‐M cycles performed between January 2012 and December 2024, comprising 137 cycles with male ADPKD, 51 cycles with female ADPKD, and 302 non‐ADPKD control cycles for other monogenic disorders. Embryologic and clinical outcomes were analyzed using denominator‐aware generalized linear mixed models and logistic regression. Sensitivity, mediation, and interaction analyses were performed to explore the role of progressive sperm motility. Results: Compared with controls, male ADPKD was associated with a lower Day 3 high‐quality embryo rate (adjusted odds ratio [OR] 0.55, 95% confidence interval [CI]: 0.34–0.90, p = 0.017) and clinical pregnancy rate per embryo transfer (adjusted OR 0.46, 95% CI: 0.28–0.74, p = 0.002). In the primary analysis, the live birth rate per embryo transfer did not differ statistically (adjusted OR 0.62, 95% CI: 0.39–1.00, p = 0.052). The association with blastocyst formation was not statistically significant after adjustment for semen parameters (adjusted OR 0.76, 95% CI: 0.55–1.04, p = 0.090), but became significant when progressive sperm motility was omitted from the model (OR 0.67, 95% CI: 0.51–0.89, p = 0.005). An exploratory interaction was detected between male ADPKD and progressive sperm motility (interaction OR 1.81, 95% CI: 1.23–2.66, p = 0.003). No significant differences in the primary embryologic or clinical outcomes were observed between female ADPKD and control cycles. Discussion: Associations with Day 3 embryo morphology and clinical pregnancy were not accompanied by a statistically significant difference in live birth in the primary analysis. Because semen quality differed substantially between groups and no non‐ADPKD group with comparably severe asthenozoospermia was included, these analyses do not establish an ADPKD‐specific effect on embryo development or overall PGT‐M success. Conclusion: The findings identify associations with selected intermediate outcomes, but do not demonstrate that male ADPKD independently impairs clinically definitive PGT‐M outcomes. The sperm motility analyses should be considered exploratory and hypothesis‐generating.

Women with polycystic ovary syndrome (PCOS) have a high incidence of pregnancy and obstetric complications. Anti-Müllerian hormone (AMH) is closely related to reproductive outcomes. The potential relationship between AMH levels and the occurrence of late miscarriage in these patients remains unclear. This study enrolled 1,831 patients diagnosed with PCOS who achieved clinical pregnancy following their first frozen-thawed embryo transfer cycles. The patients were categorized into miscarriage group and live birth group according to their pregnancy outcomes. The relationship between AMH levels and the occurrence of late miscarriage in this population was assessed before and after propensity score matching. PCOS patients with late miscarriage exhibited elevated AMH levels compared with those who had a live birth. According to univariate logistic regression analysis, each 1 ng/mL elevation in AMH level was related to a 6.3% increased risk of late miscarriage (odds ratio [OR], 1.063; 95% CI, 1.027-1.101; P = 0.001). After adjustment for confounding factors, the risk of late miscarriage increased by 5.6% (adjusted OR = 1.056, 95% CI: 1.012-1.101, adjusted P = 0.011). The odds of late miscarriage increased by 63.5% in the 50th percentile group (OR, 1.635; 95%CI, 1.129-2.369; P = 0.009), by 68.0% in the 75th percentile group (OR, 1.680; 95%CI, 1.141-2.474; P = 0.009) and by 93.8% in the 90th percentile group (OR, 1.938; 95%CI, 1.164-3.228; P = 0.011) when compared to the live birth group. After PSM, circulating AMH levels remained strongly linked to the occurrence of late miscarriage. The AUC of AMH for predicting late miscarriage was 0.614 (95% CI, 0.564-0.664; P = 0.000), with an optimal cutoff value of 10.395 ng/mL. High pre-pregnancy circulating AMH levels (especially > 10.395ng/mL) is associated with a high risk of late miscarriage in patients with PCOS undergoing FET. N/A.

Air pollutants such as fine particulate matter (PM_2.5) may be linked to the increasing prevalence of infertility.

AMH is a dependable indicator of ovarian reserve function and assessment of ovarian responsiveness. The relationship between reduced ovarian reserve and pregnancy loss remains poorly understood and requires further investigation. Currently, it has not been systematically evaluated in populations with PGT which could exclude the influence of embryonic chromosomal abnormalities on the outcomes. This study enrolled 1982 non-PCOS patients who underwent PGT and had their first frozen-thawed embryo euploidy blastocyst transfer between January 2016 and August 2023. Primary outcomes included early pregnancy loss rates (defined as spontaneous miscarriage during the early first trimester) with secondary outcomes encompassing clinical pregnancy rates and live birth rates. The cohort was divided into three subgroups using quintile-based categorization of AMH levels: low (≤ 1.872 ng/mL, n = 260); medium (1.873–5.276 ng/mL, n = 779); high (≥ 5.277 ng/mL, n = 258). After propensity score matching, 143 patients in each group were ultimately included in the current research. The matched data revealed a higher rate of EPL in the low AMH level group and a lower rate of clinical pregnancy and live births (P < 0.05). Compared to the medium AMH level group, the low AMH group had a considerably higher risk of EPL, with an unadjusted OR of 1.76 (95% CI, 1.10–2.82) and an adjusted OR of 1.85 (95% CI, 1.13–3.04). A significant association between low AMH levels and EPL was also found in the < 35 subgroup. Moreover, there was no discernible non-linear relationship between AMH levels and EPL rates in the restricted cubic spline (P-non-linear = 0.356). Subgroup analyses demonstrated the effect of AMH levels on EPL was more significant in younger patients, those with primary infertility, AFC ≥ 10, and transferred with D6 blastocysts. In non-PCOS women < 35 years undergoing euploid blastocyst transfer, low AMH (≤ 1.8 ng/mL) independently predicts EPL risk. AMH could as a biomarker of oocyte competence beyond chromosomal integrity. Future research should focus on mechanistic studies to elucidate non-chromosomal pathways linking AMH to pregnancy loss. Not applicable.

Objective: To evaluate the predictive performance of a convolutional neural network for analyzing electronic medical records in assisted reproductive therapy and to compare its accuracy and interpretability with traditional machine learning models. The study also explores the feasibility of deploying such models in resource-limited clinical settings.Design: Retrospective cohort study based on EMR data using five models: CNN, Naïve Bayes, Random Forest, Decision Tree, and Feedforward Neural Network. Feature importance and model interpretability were evaluated using SHAP.Setting: First Hospital of Zhengzhou University.Population: 48,514 fresh IVF cycles from August 2009 to May 2018.Methods: Preprocessed EMR data were used to train and evaluate five classification models predicting live birth outcomes. Stratified 5-fold cross-validation was performed for robust performance estimation. ROC curves and AUC values were used for comparative evaluation.Main Outcome Measure: Live birth.Results: The CNN model achieved an accuracy of 0.9394 ± 0.0013, AUC of 0.8899 ± 0.0032, precision of 0.9348 ± 0.0018, recall of 0.9993 ± 0.0012, and F1 score of 0.9660 ± 0.0007. Its performance was comparable to Random Forest (accuracy: 0.9406 ± 0.0017, AUC: 0.9734 ± 0.0012), and superior to Decision Tree, Naïve Bayes, and Feedforward Neural Network in recall and robustness. CNN demonstrated stable convergence during training, and SHAP-based interpretation highlighted maternal age, BMI, antral follicle count, and gonadotropin dosage as the top predictors for live birth outcome.Conclusions: With appropriate input transformation, CNNs can effectively model structured EMR data and offer predictive performance comparable to ensemble methods. Their scalability, high sensitivity, and interpretability make CNNs promising candidates for integration into clinical workflows, particularly in environments with limited computational resources.

Background: Accumulative prior studies have demonstrated that immune inflammation profoundly influences reproductive disorders of mesodermal origin. However, little is known about the causal relationship between immune factors and diseases of the reproductive system. Methods: Thorough two-sample Mendelian randomization (MR) analyses were conducted to determine the causal effects of 731 immune traits on reproductive ill-health, including abnormal spermatozoa (AS), polycystic ovary syndrome (PCOS), and spontaneous abortion (SA). Causal links were decrypted using genome-wide association study (GWAS) data. Sensitivity analyses were performed to assess the strength, heterogeneity, and horizontal pleiotropy of the results. Results: For AS, 34 causal relationships were identified, with BAFF-R, CD20, and CD27 in the B-cell panel having protective effects against AS. A crucial causative connection between CD11c+ CD62L− monocyte%monocyte (cDC panel) and AS pathogenesis was also revealed. For PCOS, 40 causal effects were established, with CD20, CD24, and CD27 in the B-cell panel playing different roles in PCOS. CD4 on CM CD4+ (maturation stages of the T-cell panel) significantly increased the risk of PCOS. For SA, 33 causative associations were determined, and a protective effect of CCR2 (C-C chemokine receptor type 2) on CD14+ CD16+ monocytes (monocyte panel) in SA was particularly noted. The diverse functions of the CD28, CD39, and CD25 molecules in the Treg cell panel in SA were also observed. Conclusion: This study comprehensively evaluated the causal impact of immune traits on reproductive illnesses, stressing the complex and important role of immunogenic factors in pathogenesis and highlighting a novel direction for clinical work.